hvanhovell commented on code in PR #49111:
URL: https://github.com/apache/spark/pull/49111#discussion_r1942207117
##########
connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala:
##########
@@ -471,16 +481,120 @@ private class KeyValueGroupedDatasetImpl[K, V, IK, IV](
}
}
+ private def aggUntypedWithValueMapFunc(columns: TypedColumn[_, _]*):
Dataset[_] = {
+ val originalDs = sparkSession.newDataset(ivEncoder, plan)
+
+ // Apply the value transformation, get a DS of two columns "iv" and "v".
+ // If any of "iv" or "v" consists of a single primitive field, wrap it
with a struct so it
+ // would not be flattened.
+ // Also here we detect if the input "iv" is a single field struct. If yes,
we rename the field
+ // to "key" to align with Spark behaviour.
+ val (valueTransformedDf, ivFields, vFields) =
+ renameSingleFieldStruct(applyValueMapFunc(originalDs))
+
+ // Rewrite grouping expressions to use "iv" as input.
Review Comment:
You could also solve this by generating the key in the map method as well.
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